{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "224d18b3",
   "metadata": {},
   "source": [
    "## 电商网站订单数据分析"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63751534",
   "metadata": {},
   "source": [
    "### 商业模式\n",
    "\n",
    "1. B2B：商家对商家（企业卖家对企业买家），交易双方都是企业，最典型的案例就是阿里巴巴，汇聚了各行业的供应商，特点是订单量一般较大。\n",
    "2. B2C：商家对个人（企业卖家对个人买家），例如：唯品会，聚美优品。\n",
    "3. B2B2C：商家对商家对个人，例如：天猫、京东。\n",
    "4. C2C：个人（卖家）对个人（买家），例如：淘宝、人人车。\n",
    "5. O2O：线上（售卖）到线下（提货），将线下的商务机会与互联网结合，让互联网成为线下交易的平台，让消费者在享受线上优惠价格的同时，又可享受线下贴心的服务，例如：美团、苏宁易购、大众点评。\n",
    "6. C2B：个人对商家（个人买家对企业卖家），先有消费者提出需求，后有商家按需求组织生产，例如：尚品宅配。\n",
    "7. 其他：ABC（代理-商家-消费者）、F2C（工厂-个人）、B2G（政府采购）、BoB（供应商-运营者-采购商）、SoLoMo（社交-本地化-移动端）……。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db346b90",
   "metadata": {},
   "source": [
    "### 核心指标\n",
    "\n",
    "指标，具备业务含义，能够对业务进行量化的统计数据，有几个要点：\n",
    "\n",
    "1. 指标必须是数值，不能是文本、日期等。\n",
    "2. 指标都是汇总计算出来的，单个明细数据不是指标。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "860218c6",
   "metadata": {},
   "source": [
    "<img src=\"resources/indicator_1.png\" width=\"85%\">"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "052167f8",
   "metadata": {},
   "source": [
    "<img src=\"resources/indicator_2.png\" width=\"85%\">"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a99befc",
   "metadata": {},
   "source": [
    "<img src=\"resources/indicator_3.png\" width=\"85%\">"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "661b4924",
   "metadata": {},
   "source": [
    "电商网站核心指标：\n",
    "\n",
    "1. 复购率和回购率\n",
    "\n",
    "    - 复购率：复购（某段时间有2次及以上购买行为）用户的占比。复购率能反映用户的忠诚度，监测周期一般较长。\n",
    "    - 回购率：回购率一般监测周期较短，可以反映如短期促销活动对用户的吸引力。\n",
    "\n",
    "2. 用户交易常用指标\n",
    "\n",
    "    - 访问次数（PV）：一定时间内某个页面的浏览次数。\n",
    "    - 访问人数（UV）：一定时间内访问某个页面的人数。\n",
    "    - 加购数：将某款商品加入到购物车的用户数。\n",
    "    - 收藏数：收藏某款商品的用户数。\n",
    "    - GMV（总交易额、成交总额）：Gross Merchandise Volume，通常称之为“交易流水”。\n",
    "    - 客单价（ARPU）：“$ 总收入 / 总用户数 $”，某些平台也用ARPPU表示客单价。\n",
    "    - 转化率：“$ 付费用户数 / 访客数 $”。\n",
    "    - 折扣率：“$ 销售额 / 吊牌总额 $”，其中吊牌总额为：“$ 吊牌价 \\times 销量 $”。\n",
    "    - 拒退量：拒收和退货的总数量。\n",
    "    - 拒退额：拒收和退货的总金额。\n",
    "    - 实际销售额：“$ 销售额 - 拒退额 $”。\n",
    "\n",
    "3. 商品管理常用指标\n",
    "\n",
    "    - SPU数：Standard Product Unit，商品的基本信息。\n",
    "    - SKU数：Standard Keeping Unit，商品的库存信息。\n",
    "    - 售卖比：“$ GMV / 备货值 $”，了解商品流转情况，可以用于库存优化。\n",
    "    - 动销率：“$ 有销量的SKU数 / 在售SKU数 $”。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ca1359f",
   "metadata": {},
   "source": [
    "<img src=\"resources/eshop-db.png\">"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d4b041c",
   "metadata": {},
   "source": [
    "### 常用模型\n",
    "\n",
    "1. RFM模型\n",
    "\n",
    "RFM模型是使用得较为广泛的客户关系管理分析模式。RFM模型是衡量客户价值和客户创利能力的重要工具和手段，通过一个客户的近期购买行为、购买的频率以及花钱的多少三项指标来描述该客户的价值状况。\n",
    "\n",
    "在RFM模式中，R（Recency）表示客户最近一次购买的时间有多远，F（Frequency）表示客户在最近一段时间内购买的次数，M（Monetary）表示客户在最近一段时间内购买的金额。RFM模型强调以客户的行为来区分客户。利用RFM分析，我们可以做以下几件事情：\n",
    "\n",
    "1. 建立会员金字塔，区分各个级别的会员，如高级会员、中级会员、低级会员，然后针对不同级别的会员施行不同的营销策略，制定不同的营销活动。\n",
    "2. 发现流失及休眠会员，通过对流失及休眠会员的及时发现，采取营销活动，激活这些会员。\n",
    "3. 在短信、EDM（Email Direct Marketing）促销中，可以利用模型，选取最优会员。\n",
    "4. 维系老客户，提高会员的忠诚度。\n",
    "\n",
    "在使用RFM模型时，可以给三个变量不同的权重或按一定的规则进行分组，然后组合三个变量，分出不同级别的会员。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "793f8978",
   "metadata": {},
   "source": [
    "<img src=\"resources/rfm-view.jpg\" width=\"80%\">"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "091f8152",
   "metadata": {},
   "source": [
    "2. AARRR模型\n",
    "\n",
    "AARRR并不算是一种数据分析模型，而是一整套数据分析的思路和逻辑框架。AARRR模型是所有产品经理都要了解的一个数据模型。\n",
    "\n",
    "<img src=\"resources/AARRR.png\" width=\"80%\">\n",
    "\n",
    "参考链接：<https://zhuanlan.zhihu.com/p/32696403>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba2cf042",
   "metadata": {},
   "source": [
    "3. 关联分析\n",
    "\n",
    "关联分析最原始的案例来自于沃尔玛的“啤酒与尿布”。通俗意义上讲，就是买了A商品的人，又有很多人买了B商品，那么我们就可以认为A、B两个商品的关联性比较高。很多数据挖掘工具都有关联挖掘，主要使用的算法是Apriori算法，在计算的过程中会主要考察品项集、置信度、相关性这三个结果数据，以最终确定商品之间的相关性。除了Apriori算法外，还有许多其他的关联分析的算法，基本上也都是从Apriori发展而来，比如FP-growth。关联分析在零售业中并不太实用，挖掘出来的关联度比较高的商品一般都是同类商品或者同品牌的商品，像“啤酒与尿布”这种，不太容易够被挖掘出来。\n",
    "\n",
    "4. 聚类分析\n",
    "\n",
    "零售行业的聚类分析主要是指将具有相似购物行为的顾客进行群体的细分，以支持精细化的营销活动，带来更大的营销效果，节省成本。可以使用K-Means或DBScan算法进行聚类，也可以在数据仓库中根据顾客购买的商品属性进行会员的聚类分析，只需要根据系统的已经有的商品分类，把购买过相同商品类别的顾客划分到一起，这种方法可能与公司的业务更加贴近。聚类分析是进行会员精细化管理，精细化营销的基础，做好聚类分析，对企业将有很大的益处。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de18b756",
   "metadata": {},
   "source": [
    "### 贝叶斯公式\n",
    "$$\n",
    "P(A|B)=\\frac{P(A)P(B|A)}{P(B)}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dde3819d",
   "metadata": {},
   "source": [
    "### 代码实操\n",
    "\n",
    "#### 数据提取和清洗\n",
    "\n",
    "1. 提取2019年的订单数据\n",
    "2. 处理业务流程不符的数据（支付时间早于下单时间、支付时长超过30分钟、订单金额小于0、支付金额小于0）\n",
    "3. 处理渠道为空的数据（补充众数）\n",
    "4. 处理平台类型字段（去掉多余的空格，保持数据一致）\n",
    "5. 添加折扣字段，处理折扣大于1的字段（将支付金额修改为“订单金额*平均折扣”）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "2aff4294",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = 'SimHei'\n",
    "plt.rcParams['axes.unicode_minus'] = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "b6b0e13e",
   "metadata": {},
   "outputs": [],
   "source": [
    "%config InlineBackend.figure_format = 'svg'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "2a1830cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 104557 entries, 1 to 104557\n",
      "Data columns (total 10 columns):\n",
      " #   Column        Non-Null Count   Dtype         \n",
      "---  ------        --------------   -----         \n",
      " 0   orderID       104557 non-null  object        \n",
      " 1   userID        104557 non-null  object        \n",
      " 2   goodsID       104557 non-null  object        \n",
      " 3   orderAmount   104557 non-null  float64       \n",
      " 4   payment       104557 non-null  float64       \n",
      " 5   chanelID      104549 non-null  object        \n",
      " 6   platfromType  104557 non-null  object        \n",
      " 7   orderTime     104557 non-null  datetime64[ns]\n",
      " 8   payTime       104557 non-null  datetime64[ns]\n",
      " 9   chargeback    104557 non-null  object        \n",
      "dtypes: datetime64[ns](2), float64(2), object(6)\n",
      "memory usage: 8.8+ MB\n"
     ]
    }
   ],
   "source": [
    "df = pd.read_excel('data/某电商网站订单数据.xlsx', index_col='id')\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "eaeb5006",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>1</th>\n",
       "      <td>sys-2018-254118088</td>\n",
       "      <td>user-157213</td>\n",
       "      <td>PR000064</td>\n",
       "      <td>272.51</td>\n",
       "      <td>272.51</td>\n",
       "      <td>渠道-0396</td>\n",
       "      <td>APP</td>\n",
       "      <td>2018-02-14 12:20:36</td>\n",
       "      <td>2019-02-28 13:38:41</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>sys-2018-263312190</td>\n",
       "      <td>user-191121</td>\n",
       "      <td>PR000583</td>\n",
       "      <td>337.93</td>\n",
       "      <td>337.93</td>\n",
       "      <td>渠道-0765</td>\n",
       "      <td>Wech atMP</td>\n",
       "      <td>2018-08-14 09:40:34</td>\n",
       "      <td>2019-01-01 14:47:14</td>\n",
       "      <td>是</td>\n",
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       "      <th>3</th>\n",
       "      <td>sys-2018-188208169</td>\n",
       "      <td>user-211918</td>\n",
       "      <td>PR000082</td>\n",
       "      <td>905.68</td>\n",
       "      <td>891.23</td>\n",
       "      <td>渠道-0530</td>\n",
       "      <td>We c hatMP</td>\n",
       "      <td>2018-11-02 20:17:25</td>\n",
       "      <td>2019-01-19 20:06:35</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>sys-2018-203314910</td>\n",
       "      <td>user-201322</td>\n",
       "      <td>PR000302</td>\n",
       "      <td>786.27</td>\n",
       "      <td>688.88</td>\n",
       "      <td>渠道-0530</td>\n",
       "      <td>WEB</td>\n",
       "      <td>2018-11-19 10:36:39</td>\n",
       "      <td>2019-08-07 12:24:35</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>sys-2018-283989279</td>\n",
       "      <td>user-120872</td>\n",
       "      <td>PR000290</td>\n",
       "      <td>550.77</td>\n",
       "      <td>542.51</td>\n",
       "      <td>渠道-9527</td>\n",
       "      <td>APP</td>\n",
       "      <td>2018-12-26 11:19:16</td>\n",
       "      <td>2019-10-01 07:42:43</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               orderID       userID   goodsID  orderAmount  payment chanelID  \\\n",
       "id                                                                             \n",
       "1   sys-2018-254118088  user-157213  PR000064       272.51   272.51  渠道-0396   \n",
       "2   sys-2018-263312190  user-191121  PR000583       337.93   337.93  渠道-0765   \n",
       "3   sys-2018-188208169  user-211918  PR000082       905.68   891.23  渠道-0530   \n",
       "4   sys-2018-203314910  user-201322  PR000302       786.27   688.88  渠道-0530   \n",
       "5   sys-2018-283989279  user-120872  PR000290       550.77   542.51  渠道-9527   \n",
       "\n",
       "   platfromType           orderTime             payTime chargeback  \n",
       "id                                                                  \n",
       "1          APP  2018-02-14 12:20:36 2019-02-28 13:38:41          否  \n",
       "2     Wech atMP 2018-08-14 09:40:34 2019-01-01 14:47:14          是  \n",
       "3    We c hatMP 2018-11-02 20:17:25 2019-01-19 20:06:35          否  \n",
       "4          WEB  2018-11-19 10:36:39 2019-08-07 12:24:35          否  \n",
       "5          APP  2018-12-26 11:19:16 2019-10-01 07:42:43          否  "
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "394e9314",
   "metadata": {},
   "outputs": [
    {
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       "      <td>337.93</td>\n",
       "      <td>337.93</td>\n",
       "      <td>渠道-0765</td>\n",
       "      <td>Wech atMP</td>\n",
       "      <td>2018-08-14 09:40:34</td>\n",
       "      <td>2019-01-01 14:47:14</td>\n",
       "      <td>是</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>sys-2018-188208169</td>\n",
       "      <td>user-211918</td>\n",
       "      <td>PR000082</td>\n",
       "      <td>905.68</td>\n",
       "      <td>891.23</td>\n",
       "      <td>渠道-0530</td>\n",
       "      <td>We c hatMP</td>\n",
       "      <td>2018-11-02 20:17:25</td>\n",
       "      <td>2019-01-19 20:06:35</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>sys-2018-203314910</td>\n",
       "      <td>user-201322</td>\n",
       "      <td>PR000302</td>\n",
       "      <td>786.27</td>\n",
       "      <td>688.88</td>\n",
       "      <td>渠道-0530</td>\n",
       "      <td>WEB</td>\n",
       "      <td>2018-11-19 10:36:39</td>\n",
       "      <td>2019-08-07 12:24:35</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>sys-2018-283989279</td>\n",
       "      <td>user-120872</td>\n",
       "      <td>PR000290</td>\n",
       "      <td>550.77</td>\n",
       "      <td>542.51</td>\n",
       "      <td>渠道-9527</td>\n",
       "      <td>APP</td>\n",
       "      <td>2018-12-26 11:19:16</td>\n",
       "      <td>2019-10-01 07:42:43</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               orderID       userID   goodsID  orderAmount  payment channelID  \\\n",
       "id                                                                              \n",
       "1   sys-2018-254118088  user-157213  PR000064       272.51   272.51   渠道-0396   \n",
       "2   sys-2018-263312190  user-191121  PR000583       337.93   337.93   渠道-0765   \n",
       "3   sys-2018-188208169  user-211918  PR000082       905.68   891.23   渠道-0530   \n",
       "4   sys-2018-203314910  user-201322  PR000302       786.27   688.88   渠道-0530   \n",
       "5   sys-2018-283989279  user-120872  PR000290       550.77   542.51   渠道-9527   \n",
       "\n",
       "   platformType           orderTime             payTime chargeback  \n",
       "id                                                                  \n",
       "1          APP  2018-02-14 12:20:36 2019-02-28 13:38:41          否  \n",
       "2     Wech atMP 2018-08-14 09:40:34 2019-01-01 14:47:14          是  \n",
       "3    We c hatMP 2018-11-02 20:17:25 2019-01-19 20:06:35          否  \n",
       "4          WEB  2018-11-19 10:36:39 2019-08-07 12:24:35          否  \n",
       "5          APP  2018-12-26 11:19:16 2019-10-01 07:42:43          否  "
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 0. 修改有问题的列名\n",
    "df.rename(columns={'chanelID': 'channelID', 'platfromType': 'platformType'}, inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "13d90f52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>orderID</th>\n",
       "      <th>userID</th>\n",
       "      <th>goodsID</th>\n",
       "      <th>orderAmount</th>\n",
       "      <th>payment</th>\n",
       "      <th>channelID</th>\n",
       "      <th>platformType</th>\n",
       "      <th>orderTime</th>\n",
       "      <th>payTime</th>\n",
       "      <th>chargeback</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>104553</th>\n",
       "      <td>sys-2020-268392025</td>\n",
       "      <td>user-182189</td>\n",
       "      <td>PR000082</td>\n",
       "      <td>186.37</td>\n",
       "      <td>126.21</td>\n",
       "      <td>渠道-0568</td>\n",
       "      <td>Wech atMP</td>\n",
       "      <td>2020-01-01 23:30:57</td>\n",
       "      <td>2020-01-01 23:31:09</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104554</th>\n",
       "      <td>sys-2020-213140521</td>\n",
       "      <td>user-170057</td>\n",
       "      <td>PR000603</td>\n",
       "      <td>138.81</td>\n",
       "      <td>138.81</td>\n",
       "      <td>渠道-0007</td>\n",
       "      <td>APP</td>\n",
       "      <td>2020-01-01 23:31:26</td>\n",
       "      <td>2020-01-01 23:31:36</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104555</th>\n",
       "      <td>sys-2020-274536228</td>\n",
       "      <td>user-156592</td>\n",
       "      <td>PR000405</td>\n",
       "      <td>2632.27</td>\n",
       "      <td>2632.27</td>\n",
       "      <td>渠道-0985</td>\n",
       "      <td>Wech atMP</td>\n",
       "      <td>2020-01-01 23:46:56</td>\n",
       "      <td>2020-01-01 23:47:06</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104556</th>\n",
       "      <td>sys-2020-279922239</td>\n",
       "      <td>user-173702</td>\n",
       "      <td>PR000387</td>\n",
       "      <td>1206.76</td>\n",
       "      <td>1029.46</td>\n",
       "      <td>渠道-0985</td>\n",
       "      <td>APP</td>\n",
       "      <td>2020-01-01 23:47:01</td>\n",
       "      <td>2020-01-01 23:47:48</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104557</th>\n",
       "      <td>sys-2020-250738010</td>\n",
       "      <td>user-164299</td>\n",
       "      <td>PR000525</td>\n",
       "      <td>3053.70</td>\n",
       "      <td>2982.26</td>\n",
       "      <td>渠道-0007</td>\n",
       "      <td>APP</td>\n",
       "      <td>2020-01-01 23:48:26</td>\n",
       "      <td>2020-01-01 23:49:44</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   orderID       userID   goodsID  orderAmount  payment  \\\n",
       "id                                                                        \n",
       "104553  sys-2020-268392025  user-182189  PR000082       186.37   126.21   \n",
       "104554  sys-2020-213140521  user-170057  PR000603       138.81   138.81   \n",
       "104555  sys-2020-274536228  user-156592  PR000405      2632.27  2632.27   \n",
       "104556  sys-2020-279922239  user-173702  PR000387      1206.76  1029.46   \n",
       "104557  sys-2020-250738010  user-164299  PR000525      3053.70  2982.26   \n",
       "\n",
       "       channelID platformType           orderTime             payTime  \\\n",
       "id                                                                      \n",
       "104553   渠道-0568    Wech atMP 2020-01-01 23:30:57 2020-01-01 23:31:09   \n",
       "104554   渠道-0007         APP  2020-01-01 23:31:26 2020-01-01 23:31:36   \n",
       "104555   渠道-0985    Wech atMP 2020-01-01 23:46:56 2020-01-01 23:47:06   \n",
       "104556   渠道-0985         APP  2020-01-01 23:47:01 2020-01-01 23:47:48   \n",
       "104557   渠道-0007         APP  2020-01-01 23:48:26 2020-01-01 23:49:44   \n",
       "\n",
       "       chargeback  \n",
       "id                 \n",
       "104553          否  \n",
       "104554          否  \n",
       "104555          否  \n",
       "104556          否  \n",
       "104557          否  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看最后五条\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "bde8ecaf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>orderID</th>\n",
       "      <th>userID</th>\n",
       "      <th>goodsID</th>\n",
       "      <th>orderAmount</th>\n",
       "      <th>payment</th>\n",
       "      <th>channelID</th>\n",
       "      <th>platformType</th>\n",
       "      <th>orderTime</th>\n",
       "      <th>payTime</th>\n",
       "      <th>chargeback</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>sys-2019-279103297</td>\n",
       "      <td>user-146548</td>\n",
       "      <td>PR000564</td>\n",
       "      <td>425.20</td>\n",
       "      <td>425.20</td>\n",
       "      <td>渠道-0765</td>\n",
       "      <td>Wech atMP</td>\n",
       "      <td>2019-01-01 00:12:23</td>\n",
       "      <td>2019-01-01 00:13:37</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>sys-2019-316686066</td>\n",
       "      <td>user-104210</td>\n",
       "      <td>PR000709</td>\n",
       "      <td>1764.37</td>\n",
       "      <td>1707.04</td>\n",
       "      <td>渠道-0396</td>\n",
       "      <td>We c hatMP</td>\n",
       "      <td>2019-01-01 00:23:06</td>\n",
       "      <td>2019-01-01 00:23:32</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>sys-2019-306447069</td>\n",
       "      <td>user-104863</td>\n",
       "      <td>PR000499</td>\n",
       "      <td>499.41</td>\n",
       "      <td>480.42</td>\n",
       "      <td>渠道-0007</td>\n",
       "      <td>Wech atMP</td>\n",
       "      <td>2019-01-01 01:05:50</td>\n",
       "      <td>2019-01-01 01:06:17</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>sys-2019-290267674</td>\n",
       "      <td>user-206155</td>\n",
       "      <td>PR000253</td>\n",
       "      <td>1103.00</td>\n",
       "      <td>1050.95</td>\n",
       "      <td>渠道-0330</td>\n",
       "      <td>APP</td>\n",
       "      <td>2019-01-01 01:16:12</td>\n",
       "      <td>2019-01-01 01:16:25</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>sys-2019-337079027</td>\n",
       "      <td>user-137939</td>\n",
       "      <td>PR000768</td>\n",
       "      <td>465.41</td>\n",
       "      <td>465.41</td>\n",
       "      <td>渠道-9527</td>\n",
       "      <td>AL i MP</td>\n",
       "      <td>2019-01-01 01:31:00</td>\n",
       "      <td>2019-01-01 01:31:36</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               orderID       userID   goodsID  orderAmount  payment channelID  \\\n",
       "id                                                                              \n",
       "6   sys-2019-279103297  user-146548  PR000564       425.20   425.20   渠道-0765   \n",
       "7   sys-2019-316686066  user-104210  PR000709      1764.37  1707.04   渠道-0396   \n",
       "8   sys-2019-306447069  user-104863  PR000499       499.41   480.42   渠道-0007   \n",
       "9   sys-2019-290267674  user-206155  PR000253      1103.00  1050.95   渠道-0330   \n",
       "10  sys-2019-337079027  user-137939  PR000768       465.41   465.41   渠道-9527   \n",
       "\n",
       "   platformType           orderTime             payTime chargeback  \n",
       "id                                                                  \n",
       "6     Wech atMP 2019-01-01 00:12:23 2019-01-01 00:13:37          否  \n",
       "7    We c hatMP 2019-01-01 00:23:06 2019-01-01 00:23:32          否  \n",
       "8     Wech atMP 2019-01-01 01:05:50 2019-01-01 01:06:17          否  \n",
       "9          APP  2019-01-01 01:16:12 2019-01-01 01:16:25          否  \n",
       "10      AL i MP 2019-01-01 01:31:00 2019-01-01 01:31:36          否  "
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 1. 提取2019年的订单数据\n",
    "from datetime import datetime\n",
    "\n",
    "start = datetime(2019, 1, 1)\n",
    "end = datetime(2019, 12, 31, 23, 59, 59)\n",
    "# 删除不在19年内的数据\n",
    "df.drop(index=df[df.orderTime < start].index, inplace=True)\n",
    "df.drop(index=df[df.orderTime > end].index, inplace=True)\n",
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "e5037132",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(104296, 10)"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 显示数据维度\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "4fafbe4a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(104291, 10)"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 2. 处理与业务流程不符的数据（支付时间早于下单时间、支付时长超过30分钟、订单金额小于0、支付金额小于0）\n",
    "# 删除支付时间早于下单时间的数据\n",
    "df.drop(index=df[df.payTime < df.orderTime].index, inplace=True)\n",
    "df.shape\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "4ff6d160",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(103354, 10)"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 删除支付时长超过30分钟的数据\n",
    "\n",
    "# 因为delta 是serise数据 所以用.dt转为天数和秒数\n",
    "delta = df.payTime - df.orderTime\n",
    "df.drop(index=df[(delta.dt.days > 0) | (delta.dt.seconds > 1800)].index, inplace=True)\n",
    "df.shape\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "f30704e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(103348, 10)"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 删除订单金额或支付金额小于0\n",
    "df.drop(df[(df.orderAmount < 0) | (df.payment < 0)].index, inplace=True)\n",
    "df.shape\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "a5a18287",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 3. 处理渠道为空的数据（补充众数）\n",
    "# mod() 查询出众数 加上索引[0]取其值 \n",
    "most_common_channel = df.channelID.mode()[0]\n",
    "df.channelID.fillna(value=most_common_channel, inplace=True)\n",
    "df.channelID.hasnans  # 检查是否有空值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "21b703cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>orderID</th>\n",
       "      <th>userID</th>\n",
       "      <th>goodsID</th>\n",
       "      <th>orderAmount</th>\n",
       "      <th>payment</th>\n",
       "      <th>channelID</th>\n",
       "      <th>platformType</th>\n",
       "      <th>orderTime</th>\n",
       "      <th>payTime</th>\n",
       "      <th>chargeback</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>sys-2019-279103297</td>\n",
       "      <td>user-146548</td>\n",
       "      <td>PR000564</td>\n",
       "      <td>425.20</td>\n",
       "      <td>425.20</td>\n",
       "      <td>渠道-0765</td>\n",
       "      <td>Wech atMP</td>\n",
       "      <td>2019-01-01 00:12:23</td>\n",
       "      <td>2019-01-01 00:13:37</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>sys-2019-316686066</td>\n",
       "      <td>user-104210</td>\n",
       "      <td>PR000709</td>\n",
       "      <td>1764.37</td>\n",
       "      <td>1707.04</td>\n",
       "      <td>渠道-0396</td>\n",
       "      <td>We c hatMP</td>\n",
       "      <td>2019-01-01 00:23:06</td>\n",
       "      <td>2019-01-01 00:23:32</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>sys-2019-306447069</td>\n",
       "      <td>user-104863</td>\n",
       "      <td>PR000499</td>\n",
       "      <td>499.41</td>\n",
       "      <td>480.42</td>\n",
       "      <td>渠道-0007</td>\n",
       "      <td>Wech atMP</td>\n",
       "      <td>2019-01-01 01:05:50</td>\n",
       "      <td>2019-01-01 01:06:17</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>sys-2019-290267674</td>\n",
       "      <td>user-206155</td>\n",
       "      <td>PR000253</td>\n",
       "      <td>1103.00</td>\n",
       "      <td>1050.95</td>\n",
       "      <td>渠道-0330</td>\n",
       "      <td>APP</td>\n",
       "      <td>2019-01-01 01:16:12</td>\n",
       "      <td>2019-01-01 01:16:25</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>sys-2019-337079027</td>\n",
       "      <td>user-137939</td>\n",
       "      <td>PR000768</td>\n",
       "      <td>465.41</td>\n",
       "      <td>465.41</td>\n",
       "      <td>渠道-9527</td>\n",
       "      <td>AL i MP</td>\n",
       "      <td>2019-01-01 01:31:00</td>\n",
       "      <td>2019-01-01 01:31:36</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               orderID       userID   goodsID  orderAmount  payment channelID  \\\n",
       "id                                                                              \n",
       "6   sys-2019-279103297  user-146548  PR000564       425.20   425.20   渠道-0765   \n",
       "7   sys-2019-316686066  user-104210  PR000709      1764.37  1707.04   渠道-0396   \n",
       "8   sys-2019-306447069  user-104863  PR000499       499.41   480.42   渠道-0007   \n",
       "9   sys-2019-290267674  user-206155  PR000253      1103.00  1050.95   渠道-0330   \n",
       "10  sys-2019-337079027  user-137939  PR000768       465.41   465.41   渠道-9527   \n",
       "\n",
       "   platformType           orderTime             payTime chargeback  \n",
       "id                                                                  \n",
       "6     Wech atMP 2019-01-01 00:12:23 2019-01-01 00:13:37          否  \n",
       "7    We c hatMP 2019-01-01 00:23:06 2019-01-01 00:23:32          否  \n",
       "8     Wech atMP 2019-01-01 01:05:50 2019-01-01 01:06:17          否  \n",
       "9          APP  2019-01-01 01:16:12 2019-01-01 01:16:25          否  \n",
       "10      AL i MP 2019-01-01 01:31:00 2019-01-01 01:31:36          否  "
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "c0bd76d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>orderID</th>\n",
       "      <th>userID</th>\n",
       "      <th>goodsID</th>\n",
       "      <th>orderAmount</th>\n",
       "      <th>payment</th>\n",
       "      <th>channelID</th>\n",
       "      <th>platformType</th>\n",
       "      <th>orderTime</th>\n",
       "      <th>payTime</th>\n",
       "      <th>chargeback</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>sys-2019-279103297</td>\n",
       "      <td>user-146548</td>\n",
       "      <td>PR000564</td>\n",
       "      <td>425.20</td>\n",
       "      <td>425.20</td>\n",
       "      <td>渠道-0765</td>\n",
       "      <td>Wechatmp</td>\n",
       "      <td>2019-01-01 00:12:23</td>\n",
       "      <td>2019-01-01 00:13:37</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>sys-2019-316686066</td>\n",
       "      <td>user-104210</td>\n",
       "      <td>PR000709</td>\n",
       "      <td>1764.37</td>\n",
       "      <td>1707.04</td>\n",
       "      <td>渠道-0396</td>\n",
       "      <td>Wechatmp</td>\n",
       "      <td>2019-01-01 00:23:06</td>\n",
       "      <td>2019-01-01 00:23:32</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>sys-2019-306447069</td>\n",
       "      <td>user-104863</td>\n",
       "      <td>PR000499</td>\n",
       "      <td>499.41</td>\n",
       "      <td>480.42</td>\n",
       "      <td>渠道-0007</td>\n",
       "      <td>Wechatmp</td>\n",
       "      <td>2019-01-01 01:05:50</td>\n",
       "      <td>2019-01-01 01:06:17</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>sys-2019-290267674</td>\n",
       "      <td>user-206155</td>\n",
       "      <td>PR000253</td>\n",
       "      <td>1103.00</td>\n",
       "      <td>1050.95</td>\n",
       "      <td>渠道-0330</td>\n",
       "      <td>App</td>\n",
       "      <td>2019-01-01 01:16:12</td>\n",
       "      <td>2019-01-01 01:16:25</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>sys-2019-337079027</td>\n",
       "      <td>user-137939</td>\n",
       "      <td>PR000768</td>\n",
       "      <td>465.41</td>\n",
       "      <td>465.41</td>\n",
       "      <td>渠道-9527</td>\n",
       "      <td>Alimp</td>\n",
       "      <td>2019-01-01 01:31:00</td>\n",
       "      <td>2019-01-01 01:31:36</td>\n",
       "      <td>否</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               orderID       userID   goodsID  orderAmount  payment channelID  \\\n",
       "id                                                                              \n",
       "6   sys-2019-279103297  user-146548  PR000564       425.20   425.20   渠道-0765   \n",
       "7   sys-2019-316686066  user-104210  PR000709      1764.37  1707.04   渠道-0396   \n",
       "8   sys-2019-306447069  user-104863  PR000499       499.41   480.42   渠道-0007   \n",
       "9   sys-2019-290267674  user-206155  PR000253      1103.00  1050.95   渠道-0330   \n",
       "10  sys-2019-337079027  user-137939  PR000768       465.41   465.41   渠道-9527   \n",
       "\n",
       "   platformType           orderTime             payTime chargeback  \n",
       "id                                                                  \n",
       "6      Wechatmp 2019-01-01 00:12:23 2019-01-01 00:13:37          否  \n",
       "7      Wechatmp 2019-01-01 00:23:06 2019-01-01 00:23:32          否  \n",
       "8      Wechatmp 2019-01-01 01:05:50 2019-01-01 01:06:17          否  \n",
       "9           App 2019-01-01 01:16:12 2019-01-01 01:16:25          否  \n",
       "10        Alimp 2019-01-01 01:31:00 2019-01-01 01:31:36          否  "
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 4. 处理平台类型字段（去掉多余的空格，保持数据一致）\n",
    "df['platformType'] = df.platformType.replace(r'\\s', '', regex=True).str.title()\n",
    "df.head()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "9c23a6c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([], dtype='int64', name='id')"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 5. 添加折扣字段，处理折扣大于1的字段（将支付金额修改为“订单金额*平均折扣”）\n",
    "df['discount'] = df.payment / df.orderAmount\n",
    "\n",
    "# 平均折扣\n",
    "mean_discount = df.discount[df.discount <= 1].mean()\n",
    "\n",
    "# .mask() 满足条件的 折处理 等于条件的 用条件填充1 \n",
    "df['payment'] = df.payment.mask(\n",
    "    df.discount > 1,\n",
    "    np.round(df.orderAmount * mean_discount, 2)\n",
    ")\n",
    "df[df.payment > df.orderAmount].index\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "22134e77",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.payment.mask?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "d2741d3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(103348, 11)"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "04deed72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9179310544305944"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_discount"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fc41074",
   "metadata": {},
   "source": [
    "#### 数据透视和可视化\n",
    "\n",
    "6. 交易总金额（GMV）、总销售额、实际销售额、退货率、客单价\n",
    "7. 每月GMV及趋势分析（折线图）\n",
    "8. 流量渠道来源拆解GMV占比（饼图）\n",
    "9. 周一到周日哪天的下单量最高、每天哪个时段下单量最高（柱状图）\n",
    "10. 用户复购率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "59f8b0b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>orderID</th>\n",
       "      <th>userID</th>\n",
       "      <th>goodsID</th>\n",
       "      <th>orderAmount</th>\n",
       "      <th>payment</th>\n",
       "      <th>channelID</th>\n",
       "      <th>platformType</th>\n",
       "      <th>orderTime</th>\n",
       "      <th>payTime</th>\n",
       "      <th>chargeback</th>\n",
       "      <th>discount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>sys-2019-279103297</td>\n",
       "      <td>user-146548</td>\n",
       "      <td>PR000564</td>\n",
       "      <td>425.20</td>\n",
       "      <td>425.20</td>\n",
       "      <td>渠道-0765</td>\n",
       "      <td>Wechatmp</td>\n",
       "      <td>2019-01-01 00:12:23</td>\n",
       "      <td>2019-01-01 00:13:37</td>\n",
       "      <td>否</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>sys-2019-316686066</td>\n",
       "      <td>user-104210</td>\n",
       "      <td>PR000709</td>\n",
       "      <td>1764.37</td>\n",
       "      <td>1707.04</td>\n",
       "      <td>渠道-0396</td>\n",
       "      <td>Wechatmp</td>\n",
       "      <td>2019-01-01 00:23:06</td>\n",
       "      <td>2019-01-01 00:23:32</td>\n",
       "      <td>否</td>\n",
       "      <td>0.967507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>sys-2019-306447069</td>\n",
       "      <td>user-104863</td>\n",
       "      <td>PR000499</td>\n",
       "      <td>499.41</td>\n",
       "      <td>480.42</td>\n",
       "      <td>渠道-0007</td>\n",
       "      <td>Wechatmp</td>\n",
       "      <td>2019-01-01 01:05:50</td>\n",
       "      <td>2019-01-01 01:06:17</td>\n",
       "      <td>否</td>\n",
       "      <td>0.961975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>sys-2019-290267674</td>\n",
       "      <td>user-206155</td>\n",
       "      <td>PR000253</td>\n",
       "      <td>1103.00</td>\n",
       "      <td>1050.95</td>\n",
       "      <td>渠道-0330</td>\n",
       "      <td>App</td>\n",
       "      <td>2019-01-01 01:16:12</td>\n",
       "      <td>2019-01-01 01:16:25</td>\n",
       "      <td>否</td>\n",
       "      <td>0.952811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>sys-2019-337079027</td>\n",
       "      <td>user-137939</td>\n",
       "      <td>PR000768</td>\n",
       "      <td>465.41</td>\n",
       "      <td>465.41</td>\n",
       "      <td>渠道-9527</td>\n",
       "      <td>Alimp</td>\n",
       "      <td>2019-01-01 01:31:00</td>\n",
       "      <td>2019-01-01 01:31:36</td>\n",
       "      <td>否</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               orderID       userID   goodsID  orderAmount  payment channelID  \\\n",
       "id                                                                              \n",
       "6   sys-2019-279103297  user-146548  PR000564       425.20   425.20   渠道-0765   \n",
       "7   sys-2019-316686066  user-104210  PR000709      1764.37  1707.04   渠道-0396   \n",
       "8   sys-2019-306447069  user-104863  PR000499       499.41   480.42   渠道-0007   \n",
       "9   sys-2019-290267674  user-206155  PR000253      1103.00  1050.95   渠道-0330   \n",
       "10  sys-2019-337079027  user-137939  PR000768       465.41   465.41   渠道-9527   \n",
       "\n",
       "   platformType           orderTime             payTime chargeback  discount  \n",
       "id                                                                            \n",
       "6      Wechatmp 2019-01-01 00:12:23 2019-01-01 00:13:37          否  1.000000  \n",
       "7      Wechatmp 2019-01-01 00:23:06 2019-01-01 00:23:32          否  0.967507  \n",
       "8      Wechatmp 2019-01-01 01:05:50 2019-01-01 01:06:17          否  0.961975  \n",
       "9           App 2019-01-01 01:16:12 2019-01-01 01:16:25          否  0.952811  \n",
       "10        Alimp 2019-01-01 01:31:00 2019-01-01 01:31:36          否  1.000000  "
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "521f30ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GMV: 10852.72万元\n",
      "总销售额: 10263.04万元\n",
      "实际销售额: 8894.04万元\n"
     ]
    }
   ],
   "source": [
    "# 6. 交易总金额（GMV）、总销售额、实际销售额、退货率、客单价\n",
    "gmv = df.orderAmount.sum()\n",
    "sales = df.payment.sum()\n",
    "real = df[df.chargeback == '否'].payment.sum()\n",
    "print(f'GMV: {gmv / 10000:.2f}万元')\n",
    "print(f'总销售额: {sales / 10000:.2f}万元')\n",
    "print(f'实际销售额: {real / 10000:.2f}万元')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "d0803fa4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "退货率: 13.18%\n",
      "客单价：1130.82元\n"
     ]
    }
   ],
   "source": [
    "back_rate = df[df.chargeback == '是'].orderID.count() / df.orderID.count()\n",
    "arppu = real / df.userID.nunique()\n",
    "print(f'退货率: {back_rate * 100:.2f}%')\n",
    "print(f'客单价：{arppu:.2f}元')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "58c481a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
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       "z\r\n",
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       "z\r\n",
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       "     <use x=\"250\" xlink:href=\"#SimHei-37\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "   <g id=\"text_26\">\r\n",
       "    <!-- 576.15 -->\r\n",
       "    <g transform=\"translate(57.821449 188.027535)scale(0.1 -0.1)\">\r\n",
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       "     <use x=\"100\" xlink:href=\"#SimHei-36\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-2e\"/>\r\n",
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       "     <use x=\"250\" xlink:href=\"#SimHei-35\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
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       "    <!-- 552.89 -->\r\n",
       "    <g transform=\"translate(103.937151 171.903151)scale(0.1 -0.1)\">\r\n",
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       "     <use x=\"200\" xlink:href=\"#SimHei-38\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-39\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
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       "    <!-- 458.58 -->\r\n",
       "    <g transform=\"translate(103.937151 216.432447)scale(0.1 -0.1)\">\r\n",
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       "     <use x=\"150\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-35\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-38\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "   <g id=\"text_29\">\r\n",
       "    <!-- 681.16 -->\r\n",
       "    <g transform=\"translate(150.052854 140.913119)scale(0.1 -0.1)\">\r\n",
       "     <use xlink:href=\"#SimHei-36\"/>\r\n",
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       "     <use x=\"200\" xlink:href=\"#SimHei-31\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-36\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "   <g id=\"text_30\">\r\n",
       "    <!-- 567.68 -->\r\n",
       "    <g transform=\"translate(150.052854 190.073887)scale(0.1 -0.1)\">\r\n",
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       "     <use x=\"200\" xlink:href=\"#SimHei-36\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-38\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "   <g id=\"text_31\">\r\n",
       "    <!-- 731.59 -->\r\n",
       "    <g transform=\"translate(196.168556 128.729231)scale(0.1 -0.1)\">\r\n",
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       "     <use x=\"100\" xlink:href=\"#SimHei-31\"/>\r\n",
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       "     <use x=\"200\" xlink:href=\"#SimHei-35\"/>\r\n",
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       "    </g>\r\n",
       "   </g>\r\n",
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       "    <!-- 605.27 -->\r\n",
       "    <g transform=\"translate(196.168556 180.992143)scale(0.1 -0.1)\">\r\n",
       "     <use xlink:href=\"#SimHei-36\"/>\r\n",
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       "     <use x=\"100\" xlink:href=\"#SimHei-35\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-32\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-37\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "   <g id=\"text_33\">\r\n",
       "    <!-- 1001.28 -->\r\n",
       "    <g transform=\"translate(239.784259 63.572127)scale(0.1 -0.1)\">\r\n",
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       "     <use x=\"100\" xlink:href=\"#SimHei-30\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-31\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-32\"/>\r\n",
       "     <use x=\"300\" xlink:href=\"#SimHei-38\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "   <g id=\"text_34\">\r\n",
       "    <!-- 817.95 -->\r\n",
       "    <g transform=\"translate(242.284259 129.608655)scale(0.1 -0.1)\">\r\n",
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       "     <use x=\"100\" xlink:href=\"#SimHei-37\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-39\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-35\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "   <g id=\"text_35\">\r\n",
       "    <!-- 1055.42 -->\r\n",
       "    <g transform=\"translate(285.899961 50.491903)scale(0.1 -0.1)\">\r\n",
       "     <use xlink:href=\"#SimHei-31\"/>\r\n",
       "     <use x=\"50\" xlink:href=\"#SimHei-30\"/>\r\n",
       "     <use x=\"100\" xlink:href=\"#SimHei-35\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-35\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-34\"/>\r\n",
       "     <use x=\"300\" xlink:href=\"#SimHei-32\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "   <g id=\"text_36\">\r\n",
       "    <!-- 870.14 -->\r\n",
       "    <g transform=\"translate(288.399961 116.999551)scale(0.1 -0.1)\">\r\n",
       "     <use xlink:href=\"#SimHei-38\"/>\r\n",
       "     <use x=\"50\" xlink:href=\"#SimHei-37\"/>\r\n",
       "     <use x=\"100\" xlink:href=\"#SimHei-30\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-31\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-34\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "   <g id=\"text_37\">\r\n",
       "    <!-- 1026.68 -->\r\n",
       "    <g transform=\"translate(332.015664 57.435487)scale(0.1 -0.1)\">\r\n",
       "     <use xlink:href=\"#SimHei-31\"/>\r\n",
       "     <use x=\"50\" xlink:href=\"#SimHei-30\"/>\r\n",
       "     <use x=\"100\" xlink:href=\"#SimHei-32\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-36\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-36\"/>\r\n",
       "     <use x=\"300\" xlink:href=\"#SimHei-38\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "   <g id=\"text_38\">\r\n",
       "    <!-- 829.98 -->\r\n",
       "    <g transform=\"translate(334.515664 126.702207)scale(0.1 -0.1)\">\r\n",
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       "     <use x=\"150\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-39\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-38\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "   <g id=\"text_39\">\r\n",
       "    <!-- 1055.37 -->\r\n",
       "    <g transform=\"translate(378.131366 50.503983)scale(0.1 -0.1)\">\r\n",
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       "     <use x=\"100\" xlink:href=\"#SimHei-35\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-35\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-33\"/>\r\n",
       "     <use x=\"300\" xlink:href=\"#SimHei-37\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
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       "    <!-- 854.72 -->\r\n",
       "    <g transform=\"translate(380.631366 120.725023)scale(0.1 -0.1)\">\r\n",
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       "     <use x=\"50\" xlink:href=\"#SimHei-35\"/>\r\n",
       "     <use x=\"100\" xlink:href=\"#SimHei-34\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-37\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-32\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "   <g id=\"text_41\">\r\n",
       "    <!-- 970.87 -->\r\n",
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       "     <use x=\"50\" xlink:href=\"#SimHei-37\"/>\r\n",
       "     <use x=\"100\" xlink:href=\"#SimHei-30\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-38\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-37\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
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       "    <!-- 791.46 -->\r\n",
       "    <g transform=\"translate(426.747069 136.008639)scale(0.1 -0.1)\">\r\n",
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       "     <use x=\"50\" xlink:href=\"#SimHei-39\"/>\r\n",
       "     <use x=\"100\" xlink:href=\"#SimHei-31\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-34\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-36\"/>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
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       "    <!-- 938.11 -->\r\n",
       "    <g transform=\"translate(472.862771 78.833999)scale(0.1 -0.1)\">\r\n",
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       "     <use x=\"100\" xlink:href=\"#SimHei-38\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-31\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-31\"/>\r\n",
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       "     <use x=\"100\" xlink:href=\"#SimHei-31\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-34\"/>\r\n",
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       "     <use x=\"100\" xlink:href=\"#SimHei-38\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-30\"/>\r\n",
       "     <use x=\"200\" xlink:href=\"#SimHei-2e\"/>\r\n",
       "     <use x=\"250\" xlink:href=\"#SimHei-39\"/>\r\n",
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       "     <use x=\"100\" xlink:href=\"#SimHei-39\"/>\r\n",
       "     <use x=\"150\" xlink:href=\"#SimHei-2e\"/>\r\n",
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       "     <use x=\"150\" xlink:href=\"#SimHei-33\"/>\r\n",
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       "\" id=\"SimHei-9645\" transform=\"scale(0.015625)\"/>\r\n",
       "      </defs>\r\n",
       "      <use xlink:href=\"#SimHei-5b9e\"/>\r\n",
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       "     </g>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "  </g>\r\n",
       " </g>\r\n",
       " <defs>\r\n",
       "  <clipPath id=\"pdb4acc52f5\">\r\n",
       "   <rect height=\"217.44\" width=\"558\" x=\"47.457812\" y=\"22.809375\"/>\r\n",
       "  </clipPath>\r\n",
       " </defs>\r\n",
       "</svg>\r\n"
      ],
      "text/plain": [
       "<Figure size 1200x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 7. 每月GMV及趋势分析（折线图）\n",
    "df['month'] = df.orderTime.dt.month\n",
    "x = [f'{x}月' for x in range(1, 13)]\n",
    "gmv_ser = np.round(df.groupby('month').orderAmount.sum() / 10000, 2)\n",
    "sales_ser = np.round(df.groupby('month').payment.sum() / 10000, 2)\n",
    "real_ser = np.round(df[df.chargeback == '否'].groupby('month').payment.sum() / 10000, 2)\n",
    "\n",
    "plt.figure(figsize=(10, 4), dpi=120)\n",
    "plt.plot(x, gmv_ser, marker='^', color='red', label='GMV')\n",
    "plt.plot(x, sales_ser, marker='o', color='green', label='销售额')\n",
    "plt.plot(x, real_ser, marker='*', color='blue', label='实际销售额')\n",
    "for i in range(12):\n",
    "    plt.text(i, gmv_ser[i + 1] + 30, gmv_ser[i + 1], ha='center')\n",
    "    plt.text(i, real_ser[i + 1] - 60, real_ser[i + 1], ha='center')\n",
    "plt.yticks(np.arange(300, 1201, 100))\n",
    "plt.xlabel('月份')\n",
    "plt.ylabel('金额（万元）')\n",
    "plt.title('2019年GMV走势图')\n",
    "plt.legend(loc='lower right')\n",
    "plt.grid(axis='y', alpha=0.25, linestyle='--')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "829c0d76",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.doubanio.com/simple"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.1.3; however, version 21.3 is available.\n",
      "You should consider upgrading via the 'e:\\python39\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Requirement already satisfied: pyecharts in e:\\python39\\lib\\site-packages (1.9.0)\n",
      "Requirement already satisfied: prettytable in e:\\python39\\lib\\site-packages (from pyecharts) (2.2.0)\n",
      "Requirement already satisfied: jinja2 in e:\\python39\\lib\\site-packages (from pyecharts) (3.0.1)\n",
      "Requirement already satisfied: simplejson in e:\\python39\\lib\\site-packages (from pyecharts) (3.17.5)\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in e:\\python39\\lib\\site-packages (from jinja2->pyecharts) (2.0.1)\n",
      "Requirement already satisfied: wcwidth in e:\\python39\\lib\\site-packages (from prettytable->pyecharts) (0.2.5)\n"
     ]
    }
   ],
   "source": [
    "! pip install pyecharts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "facadac1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"13fe412c55cb461d9b4f121ed7be393f\" style=\"width:420px; height:460px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_13fe412c55cb461d9b4f121ed7be393f = echarts.init(\n",
       "                    document.getElementById('13fe412c55cb461d9b4f121ed7be393f'), 'white', {renderer: 'canvas'});\n",
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       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
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       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
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       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"line\",\n",
       "            \"name\": \"GMV\",\n",
       "            \"connectNulls\": false,\n",
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       "            \"hoverAnimation\": true,\n",
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       "            \"lineStyle\": {\n",
       "                \"show\": true,\n",
       "                \"width\": 1,\n",
       "                \"opacity\": 1,\n",
       "                \"curveness\": 0,\n",
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       "            \"areaStyle\": {\n",
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       "            \"connectNulls\": false,\n",
       "            \"symbolSize\": 4,\n",
       "            \"showSymbol\": true,\n",
       "            \"smooth\": false,\n",
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       "            \"step\": false,\n",
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       "                [\n",
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       "            \"hoverAnimation\": true,\n",
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       "                \"\\u5b9e\\u9645\\u9500\\u552e\\u989d\"\n",
       "            ],\n",
       "            \"selected\": {\n",
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       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
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       "            \"itemWidth\": 25,\n",
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       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"axis\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
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       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
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       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"type\": \"category\",\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"boundaryGap\": false,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
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       "                \"3\\u6708\",\n",
       "                \"4\\u6708\",\n",
       "                \"5\\u6708\",\n",
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       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
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       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"min\": 300,\n",
       "            \"max\": 1200,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
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       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
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       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"2019\\u5e74GMV\\u8d70\\u52bf\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_13fe412c55cb461d9b4f121ed7be393f.setOption(option_13fe412c55cb461d9b4f121ed7be393f);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x1c1d34cf940>"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pyecharts.options as opts\n",
    "from pyecharts.charts import Line\n",
    "\n",
    "line_chart = Line(init_opts=opts.InitOpts(width=\"420px\", height=\"460px\"))\n",
    "line_chart.add_xaxis(xaxis_data=x)\n",
    "line_chart.add_yaxis(\n",
    "    series_name=\"GMV\",\n",
    "    y_axis=gmv_ser\n",
    ")\n",
    "line_chart.add_yaxis(\n",
    "    series_name=\"实际销售额\",\n",
    "    y_axis=real_ser\n",
    ")\n",
    "line_chart.set_global_opts(\n",
    "    title_opts=opts.TitleOpts(title=\"2019年GMV走势\", subtitle=\"\"),\n",
    "    tooltip_opts=opts.TooltipOpts(trigger=\"axis\"),\n",
    "    xaxis_opts=opts.AxisOpts(type_=\"category\", boundary_gap=False),\n",
    "    yaxis_opts=opts.AxisOpts(min_=300, max_=1200)\n",
    ")\n",
    "line_chart.render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "b882be3c",
   "metadata": {},
   "outputs": [
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       "   </g>\r\n",
       "  </g>\r\n",
       " </g>\r\n",
       "</svg>\r\n"
      ],
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 8. 流量渠道拆解GMV占比（饼图）\n",
    "gmv_ser = df.groupby('channelID').orderAmount.sum()\n",
    "gmv_ser.nlargest(10).plot(\n",
    "    figsize=(6, 6),\n",
    "    kind='pie',\n",
    "    autopct='%.2f%%',\n",
    "    pctdistance=0.8,\n",
    "    startangle=90,\n",
    "    counterclock=False,\n",
    "    wedgeprops=dict(width=0.4, edgecolor='white'),\n",
    "    textprops=dict(fontsize=8, color='blue')\n",
    ")\n",
    "plt.ylabel('')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "0f415454",
   "metadata": {},
   "outputs": [
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       "            \"label\": {\n",
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       "                \"\\u6e20\\u9053-0168\"\n",
       "            ],\n",
       "            \"selected\": {},\n",
       "            \"type\": \"plain\",\n",
       "            \"show\": true,\n",
       "            \"top\": \"5%\",\n",
       "            \"orient\": \"horizontal\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"GMV\\u8d21\\u732eTop10\\u6e20\\u9053\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_02dfba4efd7445779946914569877011.setOption(option_02dfba4efd7445779946914569877011);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x1c1d690d0a0>"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyecharts import options as opts\n",
    "from pyecharts.charts import Pie\n",
    "from pyecharts.faker import Faker\n",
    "\n",
    "gmv_ser = df.groupby('channelID').orderAmount.sum()\n",
    "gmv_ser = gmv_ser.nlargest(10)\n",
    "data = [\n",
    "    [gmv_ser.index[i], np.round(gmv_ser.values[i] / 10000, 2)] \n",
    "    for i in range(gmv_ser.size)\n",
    "]\n",
    "\n",
    "pie_chart = Pie(init_opts=opts.InitOpts(width=\"600px\", height=\"600px\"))\n",
    "pie_chart.add(\n",
    "    \"\",\n",
    "    data,\n",
    "    radius=\"50%\",\n",
    "    center=[\"50%\", \"50%\"],\n",
    ")\n",
    "pie_chart.set_global_opts(\n",
    "    title_opts=opts.TitleOpts(title=\"GMV贡献Top10渠道\"),\n",
    "    legend_opts=opts.LegendOpts(type_=\"plain\", pos_top=\"5%\", orient=\"horizontal\"),\n",
    ")\n",
    "pie_chart.set_series_opts(label_opts=opts.LabelOpts(formatter=\"{b}: {c}\"))\n",
    "pie_chart.render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "7eb3532d",
   "metadata": {},
   "outputs": [
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       "z\r\n",
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       "z\r\n",
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       "z\r\n",
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       "     </g>\r\n",
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       "L 1150 4350 \r\n",
       "L 1150 450 \r\n",
       "L 5225 450 \r\n",
       "z\r\n",
       "\" id=\"SimHei-56db\" transform=\"scale(0.015625)\"/>\r\n",
       "       </defs>\r\n",
       "       <use xlink:href=\"#SimHei-661f\"/>\r\n",
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       "z\r\n",
       "\" id=\"SimHei-4e94\" transform=\"scale(0.015625)\"/>\r\n",
       "       </defs>\r\n",
       "       <use xlink:href=\"#SimHei-661f\"/>\r\n",
       "       <use x=\"100\" xlink:href=\"#SimHei-671f\"/>\r\n",
       "       <use x=\"200\" xlink:href=\"#SimHei-4e94\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
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       "     <g id=\"line2d_7\">\r\n",
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       "      </g>\r\n",
       "     </g>\r\n",
       "     <g id=\"text_7\">\r\n",
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       "M 2800 1950 \r\n",
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       "z\r\n",
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       "M 2900 5075 \r\n",
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       "Q 2725 4925 2900 5075 \r\n",
       "z\r\n",
       "\" id=\"SimHei-516d\" transform=\"scale(0.015625)\"/>\r\n",
       "       </defs>\r\n",
       "       <use xlink:href=\"#SimHei-661f\"/>\r\n",
       "       <use x=\"100\" xlink:href=\"#SimHei-671f\"/>\r\n",
       "       <use x=\"200\" xlink:href=\"#SimHei-516d\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "   <g id=\"matplotlib.axis_2\">\r\n",
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       "      <defs>\r\n",
       "       <path d=\"M 0 0 \r\n",
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       "     </g>\r\n",
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       "Q 825 3375 750 2687 \r\n",
       "z\r\n",
       "\" id=\"SimHei-30\" transform=\"scale(0.015625)\"/>\r\n",
       "       </defs>\r\n",
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       "     </g>\r\n",
       "    </g>\r\n",
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       "z\r\n",
       "\" id=\"SimHei-32\" transform=\"scale(0.015625)\"/>\r\n",
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   "source": [
    "# 9. 周一到周日哪天的下单量最高、每天哪个时段下单量最高（柱状图）\n",
    "df['weekday'] = (df.orderTime.dt.dayofweek + 1) % 7\n",
    "temp = pd.pivot_table(df, index='weekday', values='orderID', aggfunc='nunique')\n",
    "x = [f'星期{x}' for x in '日一二三四五六']\n",
    "plt.figure(figsize=(6, 4), dpi=120)\n",
    "plt.bar(x, temp.orderID)\n",
    "plt.show()"
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  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "fc3bf626",
   "metadata": {},
   "outputs": [
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 103348 entries, 6 to 104301\n",
      "Data columns (total 14 columns):\n",
      " #   Column        Non-Null Count   Dtype         \n",
      "---  ------        --------------   -----         \n",
      " 0   orderID       103348 non-null  object        \n",
      " 1   userID        103348 non-null  object        \n",
      " 2   goodsID       103348 non-null  object        \n",
      " 3   orderAmount   103348 non-null  float64       \n",
      " 4   payment       103348 non-null  float64       \n",
      " 5   channelID     103348 non-null  object        \n",
      " 6   platformType  103348 non-null  object        \n",
      " 7   orderTime     103348 non-null  datetime64[ns]\n",
      " 8   payTime       103348 non-null  datetime64[ns]\n",
      " 9   chargeback    103348 non-null  object        \n",
      " 10  discount      103348 non-null  float64       \n",
      " 11  month         103348 non-null  int64         \n",
      " 12  weekday       103348 non-null  int64         \n",
      " 13  hour          103348 non-null  object        \n",
      "dtypes: datetime64[ns](2), float64(3), int64(2), object(7)\n",
      "memory usage: 11.8+ MB\n"
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   ],
   "source": [
    "# 30 分钟向下取整\n",
    "df['hour'] = df.orderTime.dt.floor('30T').dt.time\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "86bf557e",
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       "Q 2325 1725 1350 75 \r\n",
       "L 800 75 \r\n",
       "z\r\n",
       "M 662 2875 \r\n",
       "Q 700 2550 937 2337 \r\n",
       "Q 1175 2125 1450 2150 \r\n",
       "Q 1725 2175 1887 2300 \r\n",
       "Q 2050 2425 2200 2725 \r\n",
       "Q 2300 3100 2250 3362 \r\n",
       "Q 2200 3625 1987 3800 \r\n",
       "Q 1775 3975 1525 3975 \r\n",
       "Q 1375 4000 1137 3900 \r\n",
       "Q 900 3800 762 3500 \r\n",
       "Q 625 3200 662 2875 \r\n",
       "z\r\n",
       "\" id=\"SimHei-39\" transform=\"scale(0.015625)\"/>\r\n",
       "       </defs>\r\n",
       "       <use xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"50\" xlink:href=\"#SimHei-39\"/>\r\n",
       "       <use x=\"100\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"150\" xlink:href=\"#SimHei-30\"/>\r\n",
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       "       <use x=\"300\" xlink:href=\"#SimHei-30\"/>\r\n",
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       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
       "    <g id=\"xtick_20\">\r\n",
       "     <g id=\"line2d_20\">\r\n",
       "      <g>\r\n",
       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"260.8875\" xlink:href=\"#m0ed9069845\" y=\"224.64\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
       "     <g id=\"text_20\">\r\n",
       "      <!-- 09:30:00 -->\r\n",
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       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
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       "      </g>\r\n",
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       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
       "    <g id=\"xtick_22\">\r\n",
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       "      </g>\r\n",
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       "       <use x=\"150\" xlink:href=\"#SimHei-33\"/>\r\n",
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       "       <use x=\"300\" xlink:href=\"#SimHei-30\"/>\r\n",
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       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
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       "      </g>\r\n",
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       "       <use x=\"100\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"150\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"200\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"250\" xlink:href=\"#SimHei-3a\"/>\r\n",
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       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
       "    <g id=\"xtick_24\">\r\n",
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       "      <g>\r\n",
       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"307.3875\" xlink:href=\"#m0ed9069845\" y=\"224.64\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
       "     <g id=\"text_24\">\r\n",
       "      <!-- 11:30:00 -->\r\n",
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       "       <use x=\"100\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"150\" xlink:href=\"#SimHei-33\"/>\r\n",
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       "       <use x=\"300\" xlink:href=\"#SimHei-30\"/>\r\n",
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       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
       "    <g id=\"xtick_25\">\r\n",
       "     <g id=\"line2d_25\">\r\n",
       "      <g>\r\n",
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       "      </g>\r\n",
       "     </g>\r\n",
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       "      <!-- 12:00:00 -->\r\n",
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       "       <use x=\"100\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"150\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"200\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"250\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"300\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"350\" xlink:href=\"#SimHei-30\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
       "    <g id=\"xtick_26\">\r\n",
       "     <g id=\"line2d_26\">\r\n",
       "      <g>\r\n",
       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"330.6375\" xlink:href=\"#m0ed9069845\" y=\"224.64\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
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       "      <!-- 12:30:00 -->\r\n",
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       "       <use x=\"100\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"150\" xlink:href=\"#SimHei-33\"/>\r\n",
       "       <use x=\"200\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"250\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"300\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"350\" xlink:href=\"#SimHei-30\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
       "    <g id=\"xtick_27\">\r\n",
       "     <g id=\"line2d_27\">\r\n",
       "      <g>\r\n",
       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"342.2625\" xlink:href=\"#m0ed9069845\" y=\"224.64\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
       "     <g id=\"text_27\">\r\n",
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       "       <use x=\"100\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"150\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"200\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"250\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"300\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"350\" xlink:href=\"#SimHei-30\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
       "    <g id=\"xtick_28\">\r\n",
       "     <g id=\"line2d_28\">\r\n",
       "      <g>\r\n",
       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"353.8875\" xlink:href=\"#m0ed9069845\" y=\"224.64\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
       "     <g id=\"text_28\">\r\n",
       "      <!-- 13:30:00 -->\r\n",
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       "       <use x=\"100\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"150\" xlink:href=\"#SimHei-33\"/>\r\n",
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       "       <use x=\"250\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"300\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"350\" xlink:href=\"#SimHei-30\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
       "    <g id=\"xtick_29\">\r\n",
       "     <g id=\"line2d_29\">\r\n",
       "      <g>\r\n",
       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"365.5125\" xlink:href=\"#m0ed9069845\" y=\"224.64\"/>\r\n",
       "      </g>\r\n",
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       "       <use x=\"100\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"150\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"200\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"250\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"300\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"350\" xlink:href=\"#SimHei-30\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
       "    <g id=\"xtick_30\">\r\n",
       "     <g id=\"line2d_30\">\r\n",
       "      <g>\r\n",
       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"377.1375\" xlink:href=\"#m0ed9069845\" y=\"224.64\"/>\r\n",
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       "       <use x=\"100\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"150\" xlink:href=\"#SimHei-33\"/>\r\n",
       "       <use x=\"200\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"250\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"300\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"350\" xlink:href=\"#SimHei-30\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
       "    <g id=\"xtick_31\">\r\n",
       "     <g id=\"line2d_31\">\r\n",
       "      <g>\r\n",
       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"388.7625\" xlink:href=\"#m0ed9069845\" y=\"224.64\"/>\r\n",
       "      </g>\r\n",
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       "       <use x=\"100\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"150\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"200\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"250\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"300\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"350\" xlink:href=\"#SimHei-30\"/>\r\n",
       "      </g>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
       "    <g id=\"xtick_32\">\r\n",
       "     <g id=\"line2d_32\">\r\n",
       "      <g>\r\n",
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       "       <use x=\"100\" xlink:href=\"#SimHei-3a\"/>\r\n",
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       "       <use x=\"200\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"250\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"300\" xlink:href=\"#SimHei-30\"/>\r\n",
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       "     <g id=\"line2d_33\">\r\n",
       "      <g>\r\n",
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       "       <use x=\"100\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"150\" xlink:href=\"#SimHei-33\"/>\r\n",
       "       <use x=\"200\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"250\" xlink:href=\"#SimHei-3a\"/>\r\n",
       "       <use x=\"300\" xlink:href=\"#SimHei-30\"/>\r\n",
       "       <use x=\"350\" xlink:href=\"#SimHei-30\"/>\r\n",
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       "      <g>\r\n",
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     "metadata": {
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     "output_type": "display_data"
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   ],
   "source": [
    "temp = pd.pivot_table(df, index='hour', values='orderID', aggfunc='nunique')\n",
    "temp.plot(figsize=(10, 4), kind='bar', y='orderID', color=np.random.rand(24, 3))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "901d766b",
   "metadata": {},
   "outputs": [
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       "      <td>2019-12-31 23:48:34</td>\n",
       "      <td>2019-12-31 23:49:04</td>\n",
       "      <td>否</td>\n",
       "      <td>0.767258</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>23:30:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>89731 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   orderID       userID   goodsID  orderAmount  payment  \\\n",
       "id                                                                        \n",
       "6       sys-2019-279103297  user-146548  PR000564       425.20   425.20   \n",
       "7       sys-2019-316686066  user-104210  PR000709      1764.37  1707.04   \n",
       "8       sys-2019-306447069  user-104863  PR000499       499.41   480.42   \n",
       "9       sys-2019-290267674  user-206155  PR000253      1103.00  1050.95   \n",
       "10      sys-2019-337079027  user-137939  PR000768       465.41   465.41   \n",
       "...                    ...          ...       ...          ...      ...   \n",
       "104295  sys-2019-345050988  user-228042  PR000449       387.78   335.26   \n",
       "104296  sys-2019-240533537  user-121909  PR000072       390.29   390.29   \n",
       "104297  sys-2019-344079195  user-182248  PR000813       831.29   766.07   \n",
       "104299  sys-2019-382387725  user-220484  PR000782      3326.83  3273.54   \n",
       "104301  sys-2019-291405901  user-298747  PR000369       442.85   339.78   \n",
       "\n",
       "       channelID platformType           orderTime             payTime  \\\n",
       "id                                                                      \n",
       "6        渠道-0765     Wechatmp 2019-01-01 00:12:23 2019-01-01 00:13:37   \n",
       "7        渠道-0396     Wechatmp 2019-01-01 00:23:06 2019-01-01 00:23:32   \n",
       "8        渠道-0007     Wechatmp 2019-01-01 01:05:50 2019-01-01 01:06:17   \n",
       "9        渠道-0330          App 2019-01-01 01:16:12 2019-01-01 01:16:25   \n",
       "10       渠道-9527        Alimp 2019-01-01 01:31:00 2019-01-01 01:31:36   \n",
       "...          ...          ...                 ...                 ...   \n",
       "104295   渠道-0396     Wechatmp 2019-12-31 23:17:36 2019-12-31 23:17:49   \n",
       "104296   渠道-0896     Wechatmp 2019-12-31 23:27:29 2019-12-31 23:27:42   \n",
       "104297   渠道-0896     Wechatmp 2019-12-31 23:32:55 2019-12-31 23:33:06   \n",
       "104299   渠道-0530          Web 2019-12-31 23:37:30 2019-12-31 23:37:44   \n",
       "104301   渠道-0283     Wechatmp 2019-12-31 23:48:34 2019-12-31 23:49:04   \n",
       "\n",
       "       chargeback  discount  month  weekday      hour  \n",
       "id                                                     \n",
       "6               否  1.000000      1        2  00:00:00  \n",
       "7               否  0.967507      1        2  00:00:00  \n",
       "8               否  0.961975      1        2  01:00:00  \n",
       "9               否  0.952811      1        2  01:00:00  \n",
       "10              否  1.000000      1        2  01:30:00  \n",
       "...           ...       ...    ...      ...       ...  \n",
       "104295          否  0.864562     12        2  23:00:00  \n",
       "104296          否  1.000000     12        2  23:00:00  \n",
       "104297          否  0.921544     12        2  23:30:00  \n",
       "104299          否  0.983982     12        2  23:30:00  \n",
       "104301          否  0.767258     12        2  23:30:00  \n",
       "\n",
       "[89731 rows x 14 columns]"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[df.chargeback == '否']\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "c785ccd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>month</th>\n",
       "      <th>1</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>1.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "</table>\n",
       "<p>70605 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "month         1   2    3    4    5   6   7   8   9    10   11   12\n",
       "userID                                                            \n",
       "user-100000  NaN NaN  NaN  NaN  NaN NaN NaN NaN NaN  1.0  NaN  NaN\n",
       "user-100003  NaN NaN  NaN  NaN  1.0 NaN NaN NaN NaN  NaN  NaN  NaN\n",
       "user-100006  NaN NaN  NaN  NaN  NaN NaN NaN NaN NaN  NaN  1.0  NaN\n",
       "user-100007  1.0 NaN  NaN  NaN  NaN NaN NaN NaN NaN  NaN  NaN  NaN\n",
       "user-100008  NaN NaN  NaN  NaN  NaN NaN NaN NaN NaN  NaN  1.0  NaN\n",
       "...          ...  ..  ...  ...  ...  ..  ..  ..  ..  ...  ...  ...\n",
       "user-299980  NaN NaN  NaN  NaN  NaN NaN NaN NaN NaN  1.0  NaN  NaN\n",
       "user-299983  NaN NaN  NaN  NaN  NaN NaN NaN NaN NaN  NaN  NaN  1.0\n",
       "user-299989  NaN NaN  NaN  1.0  NaN NaN NaN NaN NaN  NaN  1.0  NaN\n",
       "user-299992  1.0 NaN  NaN  NaN  NaN NaN NaN NaN NaN  NaN  NaN  NaN\n",
       "user-299995  NaN NaN  1.0  NaN  NaN NaN NaN NaN NaN  NaN  NaN  NaN\n",
       "\n",
       "[70605 rows x 12 columns]"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 10. 用户复购率\n",
    "temp = pd.pivot_table(df, index='userID', columns='month', values='orderID', aggfunc='nunique')\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "40be3b8f",
   "metadata": {},
   "outputs": [
    {
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       "      <td>NaN</td>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "month         1   2    3    4    5   6   7   8   9    10   11   12\n",
       "userID                                                            \n",
       "user-100000  NaN NaN  NaN  NaN  NaN NaN NaN NaN NaN  0.0  NaN  NaN\n",
       "user-100003  NaN NaN  NaN  NaN  0.0 NaN NaN NaN NaN  NaN  NaN  NaN\n",
       "user-100006  NaN NaN  NaN  NaN  NaN NaN NaN NaN NaN  NaN  0.0  NaN\n",
       "user-100007  0.0 NaN  NaN  NaN  NaN NaN NaN NaN NaN  NaN  NaN  NaN\n",
       "user-100008  NaN NaN  NaN  NaN  NaN NaN NaN NaN NaN  NaN  0.0  NaN\n",
       "...          ...  ..  ...  ...  ...  ..  ..  ..  ..  ...  ...  ...\n",
       "user-299980  NaN NaN  NaN  NaN  NaN NaN NaN NaN NaN  0.0  NaN  NaN\n",
       "user-299983  NaN NaN  NaN  NaN  NaN NaN NaN NaN NaN  NaN  NaN  0.0\n",
       "user-299989  NaN NaN  NaN  0.0  NaN NaN NaN NaN NaN  NaN  0.0  NaN\n",
       "user-299992  0.0 NaN  NaN  NaN  NaN NaN NaN NaN NaN  NaN  NaN  NaN\n",
       "user-299995  NaN NaN  0.0  NaN  NaN NaN NaN NaN NaN  NaN  NaN  NaN\n",
       "\n",
       "[70605 rows x 12 columns]"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 购买超过1 的记为复购的  小于等于1的 记为0没复购过\n",
    "def handle_rebuy_data(x):\n",
    "    if np.isnan(x):\n",
    "        return x\n",
    "    return 1 if x > 1 else 0\n",
    "\n",
    "\n",
    "temp = temp.applymap(handle_rebuy_data)\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "c385d4d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "month\n",
       "1     0.014744\n",
       "2     0.009155\n",
       "3     0.015829\n",
       "4     0.017364\n",
       "5     0.026384\n",
       "6     0.026397\n",
       "7     0.020772\n",
       "8     0.027114\n",
       "9     0.021880\n",
       "10    0.024947\n",
       "11    0.026890\n",
       "12    0.026231\n",
       "dtype: float64"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 每月复购率\n",
    "# 复购总和/购买总和\n",
    "temp.sum() / temp.count()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61ca72c3",
   "metadata": {},
   "source": [
    "#### RFM模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "46ac2e20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>userID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>user-100000</th>\n",
       "      <td>-79</td>\n",
       "      <td>1</td>\n",
       "      <td>1770.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-100003</th>\n",
       "      <td>-221</td>\n",
       "      <td>1</td>\n",
       "      <td>511.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-100006</th>\n",
       "      <td>-47</td>\n",
       "      <td>1</td>\n",
       "      <td>443.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-100007</th>\n",
       "      <td>-351</td>\n",
       "      <td>1</td>\n",
       "      <td>2162.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-100008</th>\n",
       "      <td>-45</td>\n",
       "      <td>1</td>\n",
       "      <td>4879.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299980</th>\n",
       "      <td>-74</td>\n",
       "      <td>1</td>\n",
       "      <td>389.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299983</th>\n",
       "      <td>-4</td>\n",
       "      <td>1</td>\n",
       "      <td>706.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299989</th>\n",
       "      <td>-50</td>\n",
       "      <td>2</td>\n",
       "      <td>1637.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299992</th>\n",
       "      <td>-364</td>\n",
       "      <td>1</td>\n",
       "      <td>440.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299995</th>\n",
       "      <td>-276</td>\n",
       "      <td>1</td>\n",
       "      <td>350.87</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>70605 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               R  F        M\n",
       "userID                      \n",
       "user-100000  -79  1  1770.81\n",
       "user-100003 -221  1   511.59\n",
       "user-100006  -47  1   443.55\n",
       "user-100007 -351  1  2162.14\n",
       "user-100008  -45  1  4879.94\n",
       "...          ... ..      ...\n",
       "user-299980  -74  1   389.44\n",
       "user-299983   -4  1   706.80\n",
       "user-299989  -50  2  1637.47\n",
       "user-299992 -364  1   440.17\n",
       "user-299995 -276  1   350.87\n",
       "\n",
       "[70605 rows x 3 columns]"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 先创建购买数为一\n",
    "df['F'] = 1\n",
    "\n",
    "temp = pd.pivot_table(\n",
    "    df,\n",
    "    index='userID',\n",
    "    values=['orderTime', 'payment', 'F'],\n",
    "    aggfunc={\n",
    "        'orderTime': np.max,   # 下单的最近时间\n",
    "        'payment': np.sum,     # \n",
    "        'F': np.sum\n",
    "    }\n",
    ")\n",
    "temp['R'] = (temp.orderTime - datetime(2019, 12, 31)).dt.days\n",
    "temp['M'] = temp.payment\n",
    "temp = temp[['R', 'F', 'M']]\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "c0b9c8c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "R    -148.909072\n",
       "F       1.270887\n",
       "M    1259.690355\n",
       "dtype: float64"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "8786c7eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>userID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>user-100000</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-100003</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-100006</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-100007</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-100008</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299980</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299983</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299989</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299992</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299995</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>70605 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             R  F  M\n",
       "userID              \n",
       "user-100000  1  0  1\n",
       "user-100003  0  0  0\n",
       "user-100006  1  0  0\n",
       "user-100007  0  0  1\n",
       "user-100008  1  0  1\n",
       "...         .. .. ..\n",
       "user-299980  1  0  0\n",
       "user-299983  1  0  0\n",
       "user-299989  1  1  1\n",
       "user-299992  0  0  0\n",
       "user-299995  0  0  0\n",
       "\n",
       "[70605 rows x 3 columns]"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 由于这里没有规定公司的评价等级 我们占时用各平均值来做界定\n",
    "temp = temp.apply(lambda x: x - x.mean())\n",
    "temp = temp.applymap(lambda x: '1' if x >= 0 else '0')\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "59e6680c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "      <th>TAG</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>userID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>user-100000</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>重要发展客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-100003</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>一般挽留客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-100006</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>一般发展客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-100007</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>重要挽留客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-100008</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>重要发展客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299980</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>一般发展客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299983</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>一般发展客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299989</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>重要价值客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299992</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>一般挽留客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user-299995</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>一般挽留客户</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>70605 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             R  F  M     TAG\n",
       "userID                      \n",
       "user-100000  1  0  1  重要发展客户\n",
       "user-100003  0  0  0  一般挽留客户\n",
       "user-100006  1  0  0  一般发展客户\n",
       "user-100007  0  0  1  重要挽留客户\n",
       "user-100008  1  0  1  重要发展客户\n",
       "...         .. .. ..     ...\n",
       "user-299980  1  0  0  一般发展客户\n",
       "user-299983  1  0  0  一般发展客户\n",
       "user-299989  1  1  1  重要价值客户\n",
       "user-299992  0  0  0  一般挽留客户\n",
       "user-299995  0  0  0  一般挽留客户\n",
       "\n",
       "[70605 rows x 4 columns]"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def make_tag(model):\n",
    "#    print(model)\n",
    "    tags = {\n",
    "        '111': '重要价值客户',\n",
    "        '101': '重要发展客户',\n",
    "        '011': '重要保持客户',\n",
    "        '001': '重要挽留客户',\n",
    "        '110': '一般价值客户',\n",
    "        '100': '一般发展客户',\n",
    "        '010': '一般保持客户',\n",
    "        '000': '一般挽留客户'\n",
    "    }\n",
    "    key = model['R'] + model['F'] + model['M']  # 拼接字符串\n",
    "    return tags.get(key)  # 用键取值\n",
    "\n",
    "\n",
    "temp['TAG'] = temp.apply(make_tag, axis=1)\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9108b185",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "c0d9031e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TAG\n",
       "一般价值客户     4039\n",
       "一般保持客户     1427\n",
       "一般发展客户    19776\n",
       "一般挽留客户    22204\n",
       "重要价值客户     7863\n",
       "重要保持客户     2631\n",
       "重要发展客户     5655\n",
       "重要挽留客户     7010\n",
       "Name: TAG, dtype: int64"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ser = temp.groupby('TAG').TAG.count()\n",
    "ser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "21cb1930",
   "metadata": {},
   "outputs": [
    {
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       "     <use xlink:href=\"#SimHei-91cd\"/>\r\n",
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       "     <defs>\r\n",
       "      <path d=\"M 800 75 \r\n",
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       "Q 1775 4475 2025 4375 \r\n",
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       "Q 2675 3875 2750 3662 \r\n",
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       "</svg>\r\n"
      ],
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
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   ],
   "source": [
    "ser.plot(kind='pie', autopct='%.2f%%')\n",
    "plt.show()"
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   "id": "004738af",
   "metadata": {},
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    "### 数据分析报告撰写\n",
    "\n",
    "1. Take away in 5 minutes\n",
    "2. Never make your boss think\n",
    "3. Think complex, speak simple\n",
    "4. One point in one page"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0e7132e1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
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